Cars Dataset (2010-2020)

This dataset captures detailed specifications of 10,000 cars manufactured between 2010 and 2020. It provides a comprehensive resource for various analytical and machine learning projects, including price prediction, market trend analysis, and comparative studies among different car makes and models.

The dataset includes essential attributes such as the make and model of the car, the year of manufacture, engine size, fuel type, and the price in USD. These attributes allow for in-depth analysis and modeling, facilitating insights into market trends, price prediction, and comparative studies among different car makes and models.

The car makes and models were selected from popular vehicles available in the market, reflecting consumer preferences and market availability. The prices, engine sizes, and fuel types were randomly assigned within realistic ranges, ensuring that the dataset remains representative and suitable for various analytical purposes.

Whether you are an automotive enthusiast, a data scientist, or a machine learning practitioner, this dataset offers a rich foundation for your projects. It can be used to develop machine learning models to predict car prices, analyze trends in the automotive market, compare different car makes and models, study the distribution and evolution of fuel types, or for educational purposes in data science and machine learning courses.

The data was meticulously generated using the Faker library to simulate realistic car specifications. This dataset is versatile and can be used for a wide array of projects, making it a valuable tool in your analytical and predictive endeavors.